This research aims to obtain more insight in the perception of fabric drape and how fabric drape can be cat-egorized With the current 3D virtual technologies to simulate garments the fashion and clothing industry can speed up work processes, improve accuracy and reduce material consumption in fit, design and sales. Although the interest in 3D technology is increasing, the implementation on a large scale emerges only slowly. At the threshold between physical and virtual fitting the fashion industry faces new challenges and demands re-quiring responses out of rule. The measurement of fabric drape started in the first half of the previous cen-tury, after the introduction of 3D garment simulation fabric drape gained interest from more researchers to obtain information for the virtual drape. Intensive research has been undertaken to define ‘fabric hand’, however, research is limited for the definition of fabric drape. Better understanding of how fabrics drape and how they can be selected based on their drape might contribute to the understanding of the virtually as-sessed material and accelerate the selection process of virtually, as well as digitally presented fabrics. For this research the drape coefficient of 13 fabrics, selected based on their drape, was measured with the Cusick drape tester. Images and videos of the fabrics draped on pedestals were presented to an expert tex-tile panel who were asked to define the fabric drape. From these definitions categories, as well as identifying key-words, were derived. During a group session the expert panel evaluated the drape categories and identi-fying key-words. In the next phase an expert user panel, familiar with the assessment of fabrics in a virtual environment, assessed the appropriateness of the categories and identifying key-words which were present-ed along with the fabric drape images and videos. Moreover, both panels judged the stiffness and amount of drape, next to that they indicated similar draping fabrics. The relation between the subjective assessment of drape and the drape coefficient was investigated. The agreement of the user panel with the drape categories defined and evaluated by the textile panel was high. Further, the agreement of the majority of the user panel with the identifying key-words was above 78%. A strong relation was found between the measured drape coefficient and the subjectively assessed stiffness and amount of drape. Additionally, the analysis of the fabrics combined by the panels based on drape simi-larity, as well as the analysis of the drape coefficients, confirms with previous research, that significantly dif-ferent fabrics can have a similar drape. Fabrics can be divided in drape categories based on the way they drape, and the identifying key-words are useful to distinguish between significantly different fabrics with similar fabric drape. Moreover, the cate-gories are related to the drape coefficient.
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The short-term aim of this R&D project (financed by the Centre of Expertise Creative Industries) is to develop a virtually simulated textile database that renders 3D visual representations of these fabrics. The idea is for this database to be open source and be able to interface with 3D design applications such as those of Lectra. The textile database will include a number of different digital datasets per textile that contain information about the fabric’s drape, weight, flexibility etc., to virtually render prototypes in a 3D simulated environment. As such, in building garments via a 3D software design application, designers will be able to see how a garment changes as new textiles are applied, and how textiles behave when constructed as different garments. This will take place on 3D avatars, which may be bespoke body scans, and will allow for coordinated and precise fitting and grading.
Personalization, production on-demand, and flexible manufacture facilities are growing within the European apparel sector, supported by national and regional public policy. These developments seem to embody a much waited “paradigm shift” in the fashion industry; a shift from global to local scale, from quantity to quality and from standard products to personalized services. Such values, however, are far from new, and scholars have already pointed out the similarities between emerging and pre-industrial systems of production and consumption. This article argues that in order to understand current developments in historical context, we should return to the process of industrialization of the apparel industry during the turn from the 19th to the 20th C, taking into account aspects of production as much as mediation and consumption. With this aim in mind, the article traces the rise of ready-made garments in the Netherlands and northwest Europe, and the associated decline in custom- and home-made garments in the region. Although available statistical data is insufficient to accurately map these phenomena, secondary sources suggest that both processes were not simultaneous and therefore there was not a straightforward substitution of custom- and home-made clothing by ready-mades. While availability and trade of mass-produced ready-mades was escalating since the early 19th C, it was not until mid 20th C that custom- and home-made clothing declined among the middle class. In this study, such a gap is explained by a steady increase in the amount of clothes acquired per person: an expanding culture of consumption during the period under consideration may have enabled these different systems to flourish all together. A parallelism of the findings above with current developments suggests that we should not regard emergent industrial formats as substitutionary of established ones, but as complementary. We may then reevaluate to what extent does the rise of the flexible factory enable a “revolution”, a shift from a problematic present to a contrasting and desirable future. This historical overview indicates that, on the contrary, emerging product-service-systems manufacturing personalized garments on-demand must be considered in relation to – and in coexistence with- traditional industrial models.
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